Founder-led · technically screened
Data engineering is scarce and easy to get wrong. We technically screen data engineers for the fundamentals that keep pipelines and platforms reliable, so you meet people who can build the foundations your analytics and ML actually depend on.
Every candidate is technically assessed by us, people who have done the job, before you spend a minute interviewing.
Not sure which fits? Talk to us and we’ll recommend the right approach.
Base ranges benchmarked to our placement data at venture-backed startups and scale-ups; equity and bonus sit on top. Where a role shares the software-engineer ladder, the bands below are the reference we use. For the full picture, see our salary benchmarks.
| Level | London | Berlin | Amsterdam | New York |
|---|---|---|---|---|
| Senior Data / ML Engineer | £90k–£125k | €85k–€120k | €80k–€115k | $155k–$205k |
Salary data reviewed July 2026.
FAQ
With a realistic task close to the work — designing or reviewing a pipeline — scored against a rubric. We assess data modelling, reliability and the batch-versus-streaming trade-offs that separate a strong data engineer from someone who has only used the tools.
Yes, across the data and AI stack: data engineers, analytics engineers, data scientists and ML engineers. Our AI, ML and data recruitment page covers how we screen each.
Data and AI are the scarcest markets we recruit in for 2026, which is exactly why a genuine technical screen and an active network matter — they get you in front of strong people before everyone else.
Tell us what you’re hiring for and we’ll come back with a plan, and usually a technically screened shortlist faster than you’d expect.